Do good: Strategies for leading an inclusive data science or statistics consulting team

Pub Date : 2024-05-13 DOI:10.1002/sta4.687
Christina Maimone, Julia L. Sharp, Ofira Schwartz‐Soicher, Jeffrey C. Oliver, Lencia Beltran
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Abstract

Leading a data science or statistical consulting team in an academic environment can have many challenges, including institutional infrastructure, funding and technical expertise. Even in the most challenging environment, however, leading such a team with inclusive practices can be rewarding for the leader, the team members and collaborators. We describe nine leadership and management practices that are especially relevant to the dynamics of data science or statistics consulting teams and an academic environment: ensuring people get credit, making tacit knowledge explicit, establishing clear performance review processes, championing career development, empowering team members to work autonomously, learning from diverse experiences, supporting team members in navigating power dynamics, having difficult conversations and developing foundational management skills. Active engagement in these areas will help those who lead data science or statistics consulting groups – whether faculty or staff, regardless of title – create and support inclusive teams.
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做好事:领导包容性数据科学或统计咨询团队的策略
在学术环境中领导一个数据科学或统计咨询团队可能会面临许多挑战,包括机构基础设施、资金和专业技术知识。然而,即使在最具挑战性的环境中,以包容性的实践领导这样的团队,也能为领导者、团队成员和合作者带来丰厚的回报。我们介绍了与数据科学或统计咨询团队的动态和学术环境特别相关的九项领导和管理实践:确保人们获得荣誉、使隐性知识显性化、建立明确的绩效考核流程、支持职业发展、赋予团队成员自主工作的权力、从不同的经验中学习、支持团队成员驾驭权力动态、进行艰难的对话以及发展基础管理技能。积极参与这些领域的工作将有助于那些领导数据科学或统计咨询小组的人员--无论是教职员工,还是任何职称的人员--创建并支持包容性团队。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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